Cerebral cortex and autonomic nervous system responses during emotional memory processing.

Psychiatric symptoms are often accompanied by somatic symptoms induced by the activity of the autonomic nervous system (ANS). The aim of this study was to calculate the time lag between electroencephalography (EEG) and electrocardiography (ECG) responses, to clarify the changes in the relationship between the cerebral cortex (CC) and the sympathetic nervous system (SNS) during emotional recall processing. Twenty-two healthy young adults were examined. Their EEG and ECG data were simultaneously recorded during emotional audiovisual recall tasks using pleasant and unpleasant stimuli for 180 s, with three repetitions (Epochs 1 & 2 and Epoch 3). The EEG data were analyzed using a fast Fourier transform (FFT) to obtain a time series of relative power spectra, XE, in the theta 1, theta 2, alpha 1, alpha 2, alpha 3, beta 1, beta 2, and beta 3 bands. Time series of RR (inter-beat) intervals (time intervals between successive R waves) derived from the ECG spectral analysis using FFT was applied to the resampled time series of RR intervals over about 60 s to obtain a time series of power spectra for the ratio low frequency/high frequency (LH/HF), XC, which reflects the activity of the sympathetic nervous function. The time lag between XE and XC was calculated using wavelet-crosscorrelation analysis. The results demonstrated that the brain responded to unfamiliar emotionally pleasant stimuli in Epochs 1 & 2 earlier than the SNS, whereas the brain and SNS responded to unfamiliar unpleasant stimuli nearly simultaneously. The brain was activated rapidly in response to familiar unpleasant stimuli, although SNS responded more rapidly to familiar pleasant stimuli than the brain in Epoch 3. Our results quantitatively describe the relationship between the CC and the ANS during emotional recall.

Attention, Not Performance, Correlates With Afterdischarge Termination During Cortical Stimulation.

Cortical stimulation has been used for brain mapping for over a century, and a standard assumption is that stimulation interferes with task execution due to local effects at the stimulation site. Stimulation can however produce afterdischarges which interfere with functional localization and can lead to unwanted seizures. We previously showed that (a) cognitive effort can terminate these afterdischarges, (b) when termination thus occurs, there are electrocorticography changes throughout the cortex, not just at sites with afterdischarges or sites thought functionally important for the cognitive task used, and (c) thresholds for afterdischarges and functional responses can change among stimulation trials. We here show that afterdischarge termination can occur prior to overt performance of the cognitive tasks used to terminate them. These findings, taken together, demonstrate that task-related brain changes are not limited to one or a group of functional regions or a specific network, and not limited to the time directly surrounding overt task execution. Discrete locations, networks and times importantly underpin clinical behaviors. However, brain activity that is diffuse in location and extended in time also affect task execution and can affect brain mapping. This may in part reflect fluctuating levels of attention, engagement, or motivation during testing.

Learning process for identifying different types of communication via repetitive stimulation: feasibility study in a cultured neuronal network.

It is well known that various types of information can be learned and memorized via repetitive training. In brain information science, it is very important to determine how neuronal networks comprising neurons with fluctuating characteristics reliably learn and memorize information. The aim of this study is to investigate the learning process in cultured neuronal networks and to address the question described above. Previously, we reported that the spikes resulting from stimulation at a specific neuron propagate as a cluster of excitation waves called spike wave propagation in cultured neuronal networks. We also reported that these waves have an individual spatiotemporal pattern that varies according to the type of neuron that is stimulated. Therefore, different spike wave propagations can be identified via pattern analysis of spike trains at particular neurons. Here, we assessed repetitive stimulation using intervals of 0.5 and 1.5 ms. Subsequently, we analyzed the relationship between the repetition of the stimulation and the identification of the different spike wave propagations. We showed that the various spike wave propagations were identified more precisely after stimulation was repeated several times using an interval of 1.5 ms. These results suggest the existence of a learning process in neuronal networks that occurs via repetitive training using a suitable interval.

Asynchronous Multiplex Communication Channels in 2-D Neural Network With Fluctuating Characteristics.

Neurons behave like transistors, but have fluctuating characteristics. In this paper, we show that several asynchronous multiplex communication channels can be established in a 2-D mesh neural network with randomly generated weights between eight neighbors. Neurons were simulated by integrate-and-fire neuron models without leakage and with fluctuating refractory period and output delay. If one of the transmitting neuron groups is stimulated, the signal is propagated in the form of spike waves. The corresponding receiving neuron group is able to identify the signal after having learned to form an asynchronous multiplex communication channel. The channel is composed of many intermediate/interstitial neurons working as relays. Each neuron can work as an I/O and as a relay element, i.e., as a multiuse unit. Grouping and synchronic firing is often seen in natural neuronal networks and seems to be effective for stable/robust communication in conjunction with spatial multiplex communication. This communication pattern corresponds to our wet lab experiments on cultured neuronal networks and is similar to sound identification by the ear and mobile adaptive communication systems.

Effect of correlating adjacent neurons for identifying communications: Feasibility experiment in a cultured neuronal network.

Neuronal networks have fluctuating characteristics, unlike the stable characteristics seen in computers. The underlying mechanisms that drive reliable communication among neuronal networks and their ability to perform intelligible tasks remain unknown. Recently, in an attempt to resolve this issue, we showed that stimulated neurons communicate via spikes that propagate temporally, in the form of spike trains. We named this phenomenon "spike wave propagation". In these previous studies, using neural networks cultured from rat hippocampal neurons, we found that multiple neurons, e.g., 3 neurons, correlate to identify various spike wave propagations in a cultured neuronal network. Specifically, the number of classifiable neurons in the neuronal network increased through correlation of spike trains between current and adjacent neurons. Although we previously obtained similar findings through stimulation, here we report these observations on a physiological level. Considering that individual spike wave propagation corresponds to individual communication, a correlation between some adjacent neurons to improve the quality of communication classification in a neuronal network, similar to a diversity antenna, which is used to improve the quality of communication in artificial data communication systems, is suggested.

Quantification of autonomic nervous activity by heart rate variability and approximate entropy in high ultrafiltration rate during hemodialysis.

BACKGROUND: Few studies have focused on the imbalance of the autonomic nervous system in ultrafiltration rate (UFR) subjects without blood pressure variation during maintenance hemodialysis (HD), although the role of autonomic nervous system activation during HD has been proposed to be an important factor for the maintenance of blood pressure. METHODS: Variations over time in autonomic nervous activity due to differences in UFR were evaluated by measuring heart rate variability (HRV) and approximate entropy (ApEn) in 35 HD patients without blood pressure variations during HD session. The subjects were divided into 3 groups, those with UFR <10 ml/h/kg; ≥10 ml/h/kg but ≤15 ml/h/kg; and >15 ml/h/kg, and Holter ECG was recorded continuously during HD session using frequency analysis of RR intervals. High frequency (HF) and low frequency (LF) spectral components are found to be representative of the parasympathetic nervous system and sympathovagal balance, respectively, with the ratio of LF to HF of HRV providing a measure of sympathetic nervous system. RESULTS: In subjects with UFR >15 ml/h/kg, HF components were significantly lower, and LF/HF and ApEn values were significantly higher, in the latter half of an HD session than before starting HD. CONCLUSION: Removing water from these subjects would promote sustained sympathetic nervous overactivity. These findings indicate that the UFR during HD needs to be set at ≤15 ml/h/kg.

Spike Code Flow in Cultured Neuronal Networks.

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Emotion Regulation of Neuroticism: Emotional Information Processing Related to Psychosomatic State Evaluated by Electroencephalography and Exact Low-Resolution Brain Electromagnetic Tomography.

Emotion regulation is the process that adjusts the type or amount of emotion when we experience an emotional situation. The aim of this study was to reveal quantitative changes in brain activity during emotional information processing related to psychosomatic states and to determine electrophysiological features of neuroticism. Twenty-two healthy subjects (mean age 25 years, 14 males and 8 females) were registered. Electroencephalography (EEG) was measured during an emotional audiovisual memory task under three conditions (neutral, pleasant and unpleasant sessions). We divided the subjects into two groups using the Cornell Medical Index (CMI): (CMI-I: control group, n = 10: CMI-II, III or IV: neuroticism group, n = 12). We analyzed the digital EEG data using exact low-resolution brain electromagnetic tomography (eLORETA) current source density (CSD) and functional connectivity analysis in several frequency bands (δ, θ, α, ß, γ and whole band). In all subjects, bilateral frontal α CSD in the unpleasant session increased compared to the pleasant session, especially in the control group (p < 0.05). CSD of the neuroticism group was significantly higher than that of the control group in the full band at the amygdala and inferior temporal gyrus, and in the α band at the right temporal lobe (p < 0.05). Additionally, we found an increase in functional connectivity between the left insular cortex and right superior temporal gyrus in all subjects during the unpleasant session compared to the pleasant session (p < 0.05). In this study, using EEG analysis, we could find a novel cortical network related to brain mechanisms underlying emotion regulation. Overall findings indicate that it is possible to characterize neuroticism electrophysiologically, which may serve as a neurophysiological marker of this personality trait. © 2015 S. Karger AG, Basel.

Comparison of EEG propagation speeds under emotional stimuli on smartphone between the different anxiety states.

The current study evaluated the effect of different anxiety states on information processing as measured by an electroencephalography (EEG) using emotional stimuli on a smartphone. Twenty-three healthy subjects were assessed for their anxiety states using The State Trait Anxiety Inventory (STAI) and divided into two groups: low anxiety (I, II) or high anxiety (III and IV, V). An EEG was performed while the participant was presented with emotionally laden audiovisual stimuli (resting, pleasant, and unpleasant sessions) and emotionally laden sentence stimuli (pleasant sentence, unpleasant sentence sessions) and EEG data was analyzed using propagation speed analysis. The propagation speed of the low anxiety group at the medial coronal for resting stimuli for all time segments was higher than those of high anxiety group. The low anxiety group propagation speeds at the medial sagittal for unpleasant stimuli in the 0-30 and 60-150 s time frames were higher than those of high anxiety group. The propagation speeds at 150 s for all stimuli in the low anxiety group were significantly higher than the correspondent propagation speeds of the high anxiety group. These events suggest that neural information processes concerning emotional stimuli differ based on current anxiety state.

Detection of M-sequences from spike sequence in neuronal networks.

In circuit theory, it is well known that a linear feedback shift register (LFSR) circuit generates pseudorandom bit sequences (PRBS), including an M-sequence with the maximum period of length. In this study, we tried to detect M-sequences known as a pseudorandom sequence generated by the LFSR circuit from time series patterns of stimulated action potentials. Stimulated action potentials were recorded from dissociated cultures of hippocampal neurons grown on a multielectrode array. We could find several M-sequences from a 3-stage LFSR circuit (M3). These results show the possibility of assembling LFSR circuits or its equivalent ones in a neuronal network. However, since the M3 pattern was composed of only four spike intervals, the possibility of an accidental detection was not zero. Then, we detected M-sequences from random spike sequences which were not generated from an LFSR circuit and compare the result with the number of M-sequences from the originally observed raster data. As a result, a significant difference was confirmed: a greater number of "0-1" reversed the 3-stage M-sequences occurred than would have accidentally be detected. This result suggests that some LFSR equivalent circuits are assembled in neuronal networks.

Random bin for analyzing neuron spike trains.

When analyzing neuron spike trains, it is always the problem of how to set the time bin. Bin width affects much to analyzed results of such as periodicity of the spike trains. Many approaches have been proposed to determine the bin setting. However, these bins are fixed through the analysis. In this paper, we propose a randomizing method of bin width and location instead of conventional fixed bin setting. This technique is applied to analyzing periodicity of interspike interval train. Also the sensitivity of the method is presented.

Afterdischarges during cortical stimulation at different frequencies and intensities.

PURPOSE: The occurrence of unwanted afterdischarges (ADs) impedes cortical stimulation for mapping purposes. We investigated the safety of several stimulation paradigms. METHODS: We compared the incidence of ADs and behavioral responses of two stimulation frequencies (50 and 100 Hz), at two intensities (1 and 0.2 ms pulse widths). RESULTS: Stimulation with 100 Hz was more likely to cause ADs than 50 Hz, and stimulation using 1 ms pulse width was more likely to cause ADs than 0.2 ms. CONCLUSIONS: Stimulation using 50 Hz frequency with a pulse width of 0.2 ms might be safer during cortical mapping.

Spatially filtered magnetoencephalographic analysis of cortical oscillatory changes in basic brain rhythms during the Japanese 'Shiritori' Word Generation Task.

BACKGROUND: 'Shiritori' (capping verses) is a traditional Japanese word generation game, and is very familiar to native Japanese speakers. The shiritori task is expected to more strongly activate temporal language-related regions than conventional word generation to letters because of its characteristic way to make cue letters. OBJECTIVES: The aim of this study was to examine the cortical oscillatory changes in basic brain rhythms during silently performing a shiritori task. METHODS: Using synthetic aperture magnetometry (SAM) analysis of magnetoencephalography, we estimated the tomographic distributions of the statistically significant differences of the power in the alpha and beta frequency bands between the resting and the task periods. RESULTS: Significant event-related desynchronization (ERD) in the 8- to 25-Hz band, thought to reflect neural activation, was localized within task-related cortical regions with left-side dominance. The significant ERDs were estimated in both the frontal and temporal language-related regions encompassing Broca's and Wernicke's areas, although previous neuroimaging studies using word generation to letters showed neural activation predominantly in frontal regions. CONCLUSIONS: Our results show the potential of SAM analysis for reliable brain mapping of language processing, and suggest that the shiritori task might be more suitable for examining the language-related network in the brain than conventional word generation to letters.

Information processing flow and neural activations in the dorsolateral prefrontal cortex in the Stroop task in schizophrenic patients. A spatially filtered MEG analysis with high temporal and spatial resolution.

Using a spatially filtered magnetoencephalography analysis (synthetic aperture magnetometry), we estimated neural activations in the Stroop task in nearly real time for schizophrenic patients with/without auditory hallucinations and for normal control subjects. In addition, auditory hallucinations were examined through the information processing flow of the brain neural network, including the frontal regions. One hundred unaveraged magnetoencephalography signals during the incongruent stimulus responses were analyzed with a time window of 200 ms in steps of 50 ms. In the 25-60-Hz band, cortical regions that showed significant current source density changes were examined for each time window. The three groups showed significantly decreased current source density, corresponding to neural activation, with temporal overlap along the fundamental cognitive information processing flow: sensory input system, executive control system, motor output system. Transient neural activations in the dorsolateral prefrontal cortex were bilateral with left-side dominancy for normal controls, left-lateralized for nonhallucinators and right-lateralized for hallucinators. Our results suggest that the dysfunction in the left dorsolateral prefrontal cortex was related to auditory hallucinations, while the information processing flow was unaffected in the schizophrenic subjects in the Stroop task.

Wavelet analysis for neonatal electroencephalographic seizures.

Electroencepholographs (EEGs) of neonatal seizures differ from those of children and adults. This study evaluated whether wavelet transform analysis, a nonstationary frequency analysis of EEG, can recognize and characterize neonatal seizures. Twenty-second segments were analyzed from 69 EEG seizures in 15 neonatal patients whose seizures lasted 10 seconds or longer. The wavelet transform results were examined, as were EEG seizure durations and dominant frequencies. The wavelet transform results were correlated with the occurrence, after an 18-month follow-up, of postneonatal seizures. Wavelet transform analysis identified 40 seizures (58%) with a "sustained dominant frequency component" that lasted 10 seconds or longer and 29 seizures without a sustained dominant frequency component. The mean seizure duration of the 40 seizures with sustained dominant frequency components was 63.3 seconds, longer than the mean duration (33.6 seconds) of the seizures without sustained dominant frequency components, P < 0.01. Eleven patients manifested postneonatal epileptic seizures. Fifty-two EEG seizures in these 11 patients revealed more sustained dominant frequency components (74%) than 17 seizures in the 4 patients without postneonatal seizures (only 12%), P < 0.05. Wavelet transform analysis can identify neonatal EEG seizures and characterize their epileptic components. The presence of sustained dominant frequency components may predict postneonatal epileptic seizures.

Parallel distributed processing neuroimaging in the Stroop task using spatially filtered magnetoencephalography analysis.

Parallel distributed processing neuroimaging in the Stroop color word interference task in five healthy subjects was studied. The total reaction time was set at 650 ms with a time window of 200 ms in steps of 50 ms. Spatially filtered magnetoencephalography analysis, as used in synthetic aperture magnetometry, was used. Neural activation began in the left posterior parietal-occipital area (150-250 ms post-stimulus), followed by the right prefrontal polar area (250-350 ms), the left dorsolateral prefrontal cortex (250-400 ms), and the mid- to lower- primary motor area (350-400 ms). Successive and temporally overlapping activation of various cortical regions were successfully estimated within a short 200 ms time interval, contrary to previous positron emission tomography and fMRI studies.

Optimizing parameters for terminating cortical afterdischarges with pulse stimulation.

PURPOSE: We previously reported that brief pulses of electrical stimulation (BPSs) can terminate afterdischarges (ADs) during cortical stimulation. We investigated conditions under which BPS is more likely to suppress ADs. METHODS: We analyzed parameters altering BPS effectiveness on 200 ADs in seven patients with implanted subdural electrodes. RESULTS: The odds of BPSs stopping ADs was 8.6 times greater at primary sites (directly stimulated electrodes) than at secondary sites (adjacent electrodes) (p = 0.016). BPS applied within 4.5 s after onset of AD had 2 times greater odds of stopping ADs (p = 0.014). BPS applied when AD voltage was negative was 1.9 times more likely to stop ADs (p = 0.012). ADs with rhythmic pattern responded best (p < 0.0001). BPS stopped 100% of ADs not starting immediately after localization stimulus (LS) versus 29% of those starting immediately (p < 0.0001). CONCLUSIONS: BPS is more likely to terminate ADs at primary electrodes, if given early, if applied to the negative peak of the AD waveform, if AD has a rhythmic pattern, and if AD did not start immediately after LS.

Wavelet-crosscorrelation analysis can help predict whether bursts of pulse stimulation will terminate afterdischarges.

OBJECTIVE: Extraoperative cortical localizing stimulation (LS) is a standard clinical tool used to assess brain function before epilepsy surgery. However, LS can produce unwanted afterdischarges (ADs). We previously have shown that brief pulses of electrical stimulation (BPS) can terminate ADs caused by cortical stimulation. Our objective was to assess whether wavelet-crosscorrelation analysis could help predict the conditions under which BPS would be most likely to terminate ADs. METHODS: We used wavelet-crosscorrelation analysis to get wavelet-correlation coefficients (WCC), and determine time lag (TL) and absolute value of TL (ATL) between two electrodes. For Analysis-1, we compared WCC and ATL in epoch 1 which was before LS, epoch 2 which was after LS but before BPS, and epoch 3 which was after BPS. For Analysis 2, we compared WCC and ATL during epoch 1 under 4 conditions: epochs when ADs subsequently terminated within 2 s after the end of BPS (1A), terminated within 2-5 s (1B), did not terminate within 5 s (1C), and when ADs did not appear (1D). RESULTS: We found that BPS efficacy in terminating ADs was predicted by (1) low correlation and (2) slow propagation speed between electrode pairs in the 2-10 s period before stimulation. CONCLUSIONS: Wavelet-crosscorrelation analysis can help predict conditions during which BPS can abort ADs. It is possible that similar analyses could help predict when BPS or other interventions could abort clinical seizures.

Landau-Kleffner Syndrome: Localization of Epileptogenic Lesion Using Wavelet- Cross-Correlation Analysis.

Magnetoencephalographic findings in a 6-year-old patient suffering from acquired aphasia with convulsive disorder (Landau-Kleffner Syndrome, LKS) are presented. The data were analyzed using wavelet-cross-correlation analysis, a nonstationary analysis method developed to analyze the localization of an epileptogenic lesion and the propagation of epileptiform discharges. The results indicate that LKS might be a disorder of the primary temporal cortex, and that the auditory neural network may function as the circuit for the epileptic discharge propagation.